{"id":"W4391960366","doi":"10.1002/spy2.380","title":"Comprehensive evaluation of privacy policies using the contextual integrity framework","year":2024,"lang":"en","type":"article","venue":"Security and Privacy","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transparency (behavior); Privacy policy; CLARITY; Computer science; Internet privacy; Information privacy; Privacy by Design; Context (archaeology); Vagueness; Set (abstract data type); Privacy software; Strengths and weaknesses; Computer security; Fuzzy logic; Psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002456505,0.0001518845,0.0002122226,0.0001049417,0.0007600147,0.0002855796,0.0005402371,0.0002231922,0.0001499614],"category_scores_gemma":[0.002794408,0.0001186674,0.00009032698,0.000491272,0.0007475237,0.0005841838,0.0004724075,0.000654457,0.000009043987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001214168,"about_ca_system_score_gemma":0.0004420648,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009224123,"about_ca_topic_score_gemma":0.0004336808,"domain_scores_codex":[0.9973997,0.0009847766,0.0002877286,0.0003006485,0.0007424019,0.0002847045],"domain_scores_gemma":[0.9983847,0.0006849208,0.0001019675,0.0003706199,0.0003676707,0.00009014384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007962593,0.000140851,0.001476287,0.0003464864,0.0001591182,0.000003213604,0.478871,0.000009583769,0.0009249188,0.4782182,0.002431105,0.03733956],"study_design_scores_gemma":[0.0003288786,0.00007602025,0.003285493,0.0003514279,0.0001958729,0.00001003026,0.02623405,0.007924109,0.0006517909,0.79487,0.165791,0.0002813581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789147,0.01005431,0.00204996,0.005891448,0.0005804401,0.0007850575,0.00006657143,0.0001125728,0.001544949],"genre_scores_gemma":[0.9977629,0.001015023,0.000441192,0.0001910061,0.0005432332,0.00001525118,0.0000102035,0.00001027891,0.00001089481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.452637,"threshold_uncertainty_score":0.9973735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1238061655696588,"score_gpt":0.4051583846328736,"score_spread":0.2813522190632148,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}